seo-audit-mcp
seo-audit-mcp
Un servidor MCP que le da a Claude (o a cualquier cliente MCP) la capacidad de auditar el SEO técnico de un sitio web en vivo: cobertura del mapa del sitio, problemas por página y cadenas de redirección.
Pide en lenguaje natural — "audita mortgagecalculatortools.com y dime de qué páginas Google nunca llega a enterarse" — y el modelo llama a las herramientas, rastrea el sitio y responde con detalles.
El problema que resuelve
El sitemap.xml de un sitio es cómo le dices a Google qué páginas existen. Cuando falta una página, nada da error y nada avisa: la página simplemente nunca acumula impresiones. Comprobarlo a mano significa comparar un listado del sistema de archivos con un archivo XML, así que en la práctica nadie lo hace.
Caso práctico: una brecha de 25 páginas que resultó ser correcta
El primer sitio al que se apuntó esto tenía 125 archivos HTML en disco y 100 URL en su mapa del sitio. Una brecha de 25 páginas — el tipo de hallazgo que se reporta como un bug y se asigna a alguien.
Una llamada a sitemap_coverage sacó a la luz la brecha, y una llamada a audit_urls sobre una muestra la explicó: cada una de las 25 llevaba <meta name="robots" content="noindex, follow">. Eran dos clústeres de contenido deliberadamente desindexados, y el mapa del sitio tenía toda la razón al omitirlos. Verificado después contra el sistema de archivos: 25 páginas noindex en disco, las mismas 25 ausentes del mapa del sitio, cero páginas noindex incluidas por error. Consistencia perfecta.
Ese es el resultado útil. Un número de cobertura a secas ("125 vs 100") se lee como un defecto y se lleva un día del tiempo de alguien; cobertura más el estado noindex por página cierra la cuestión en un minuto. Esta herramienta es tan valiosa por las falsas alarmas que elimina como por las brechas reales que encuentra — por eso audit_urls informa del noindex por página en lugar de limitarse a contar URL.
Related MCP server: web-audit-mcp
Herramientas
Herramienta | Qué hace |
| Obtiene |
| Rastrea URL concurrentemente e informa de problemas por página: estado roto, cadenas de redirección, |
| Compara un mapa del sitio con una lista de URL que sabes que existen → lo que falta en el mapa del sitio, lo que está declarado pero muerto |
| Traza cadenas de redirección, marca cadenas de varios saltos y cadenas que terminan en 4xx/5xx — úsalo después de un cambio de estructura de URL |
Cada herramienta devuelve JSON estructurado con una lista issues por página y un issue_summary agregado, de modo que el modelo pueda razonar sobre los recuentos en lugar de releer el HTML en bruto.
Instalación
pip install -e .Requiere Python 3.10+. Dependencias: mcp>=2.0.0, httpx.
Conéctalo a Claude Code
Añádelo a .mcp.json en tu proyecto (o ~/.claude.json para uso global):
{
"mcpServers": {
"seo-audit": {
"command": "python",
"args": ["-m", "seo_audit_mcp"]
}
}
}Para Claude Desktop, el mismo bloque va en claude_desktop_config.json.
Entonces solo pregunta:
Obtén el mapa del sitio de https://example.com/sitemap.xml, audita las primeras 20 URL y resume los problemas por frecuencia.
Ejecútalo directamente
python -m seo_audit_mcp # stdio transportNotas de diseño
Tres decisiones que merece la pena destacar, porque son la diferencia entre una demo y algo a lo que puedes apuntar en el sitio de producción de un cliente:
El rastreo está limitado en velocidad por diseño. fetch_many se ejecuta detrás de un asyncio.Semaphore limitado a 16 solicitudes concurrentes, y cada herramienta limita su entrada. Un mapa del sitio de 500 URL sin ese límite abriría 500 sockets a la vez y se interpretaría como un ataque al host de destino. El rastreo es un coste que paga el sitio objetivo, por lo que el límite no se puede configurar al alza desde la superficie de la herramienta.
Ningún fallo de obtención aborta una ejecución. fetch_one captura httpx.HTTPError y lo registra en el PageAudit devuelto en lugar de lanzarlo. Un host muerto en un rastreo de 200 URL degrada una fila en lugar de perder 199 resultados buenos.
El análisis sintáctico es deliberadamente permisivo. El HTML del mundo real está malformado con la frecuencia suficiente como para que un analizador estricto que lance una excepción a mitad del rastreo sea un problema. Los extractores son regex permisivas que devuelven None en lugar de lanzar una excepción — pero con las trampas controladas: los cuerpos de <script> y <style> se eliminan antes de contar palabras y extraer encabezados, de modo que un <h1> dentro de un literal de cadena JS no se cuenta como encabezado, y los enlaces canónicos relativos se resuelven contra la URL de la página.
normalize_url deliberadamente no elimina las barras finales: /a y /a/ pueden ser páginas realmente distintas, y unificarlas ocultaría problemas de contenido duplicado que esta herramienta existe para sacar a la luz.
Pruebas
pip install -e ".[dev]"
pytestEl conjunto de pruebas no usa red — HTTP se ejercita a través de httpx.MockTransport, por lo que se ejecuta en CI y en un avión. Cubre los casos límite del análisis que muerden en producción: encabezados incrustados en scripts, sitemaps sin espacio de nombres, enlaces canónicos relativos, URL de sitemap que devuelven un HTML 404 estilizado con estado 200, y tipos de contenido no HTML que se informan erróneamente como páginas "sin título".
Licencia
MIT
Available Tools
4 toolsaudit_urlsA
Crawl a list of URLs and report per-page technical SEO issues: broken status codes, redirect chains, missing or over-length titles and meta descriptions, missing or duplicate H1, missing canonical, noindex, and thin content. Returns a per-URL breakdown plus an issue summary.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes | ||
| concurrency | No | ||
| timeout_seconds | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral disclosure burden. It usefully states that the tool crawls URLs and returns a per-URL breakdown plus an issue summary, but it does not disclose operational behaviors such as crawl duration, rate limiting, redirect-following details, or auth/network requirements. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single information-dense sentence that front-loads the action and resource, then lists issue categories and the return shape. It avoids repetition and wastes no words, though the enumeration makes it slightly dense.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so the description does not need to detail return values, and it does give a useful high-level summary. However, with zero annotations, zero schema descriptions, and no usage guidance, the description leaves concurrency/timeout semantics and tool-selection boundaries undocumented, making it only moderately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it never names or explains urls, concurrency, or timeout_seconds. The parameter names are somewhat self-explanatory, yet the description adds no detail about what concurrency or timeout_seconds control, how URLs should be formatted, or whether limits apply.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb-resource pair ('Crawl a list of URLs and report per-page technical SEO issues') and then enumerates the exact issue categories. This clearly distinguishes it from siblings like fetch_sitemap and sitemap_coverage by centering on per-URL technical SEO auditing, even though it overlaps with check_redirects on redirect chains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its use case by listing SEO checks, but it never explicitly states when to prefer this over check_redirects, fetch_sitemap, or sitemap_coverage, nor does it give any 'when not to use' guidance. An agent can infer the purpose but must decide on selection criteria without direct help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_redirectsA
Trace the redirect chain for each URL and flag chains longer than one hop, redirect loops, and URLs that resolve to a 4xx/5xx. Use after a site migration or a URL-structure change.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It clearly discloses what the tool does: traces chains, flags one-hop violations, loops, and error responses. It could add operational details like network cost or rate limits, but the core behavior is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler, and the main behavior is front-loaded. The second sentence supplies a practical trigger for use. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with an output schema present, the description covers what the tool does and when to use it. It does not fully cover input format details, but the missing information is minor given the low complexity and available output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds little about the 'urls' parameter beyond saying 'for each URL.' It does not clarify expected URL format (absolute vs relative), whether schemes are required, or any limits on list length, so the agent gets almost no parameter guidance beyond the bare schema type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Trace the redirect chain for each URL' and names concrete detection outcomes (long chains, loops, 4xx/5xx). This is distinct from siblings like fetch_sitemap or audit_urls, making the tool's purpose immediately clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use after a site migration or a URL-structure change,' which gives a clear context for when this tool is appropriate. It does not mention alternatives or when not to use it, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fetch_sitemapA
Fetch and parse a sitemap.xml, following sitemap-index nesting, and return every page URL it declares. Call this first when auditing a site you do not have a URL list for.
| Name | Required | Description | Default |
|---|---|---|---|
| sitemap_url | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral burden. It discloses that the tool follows sitemap-index nesting and returns every declared page URL, which are meaningful behavioral details beyond what the schema shows. It does not mention failure modes or network behavior, but for a straightforward fetch-and-parse read operation this is reasonably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler. The first sentence states what the tool does and the second gives usage guidance. The most important behavioral details are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with an output schema present, the description is complete: it explains what the tool does, how it behaves with index nesting, what it returns, and when to call it. Nothing essential for correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It indirectly clarifies that sitemap_url should point to a sitemap.xml and that index nesting is followed, but it does not explicitly describe the URL format, required scheme, or example values. Because the single parameter is highly self-evident from the tool name and description, this is adequate but not enriched.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Fetch and parse a sitemap.xml' and the specific outcome: 'return every page URL it declares.' It also mentions the non-obvious behavior of following sitemap-index nesting, which distinguishes this from simply fetching one XML file. The phrase 'Call this first when auditing a site' also separates it from siblings like audit_urls and sitemap_coverage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides explicit guidance: 'Call this first when auditing a site you do not have a URL list for.' This clearly tells an agent when to use it. However, it does not name alternative tools or explicitly state when not to use it, so it falls just short of full usage differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sitemap_coverageA
Compare a sitemap against a list of URLs you know exist (e.g. from the filesystem or a crawl) and report which are missing from the sitemap and which the sitemap declares but are unreachable. Missing pages are pages Google is never told about.
| Name | Required | Description | Default |
|---|---|---|---|
| verify | No | ||
| known_urls | Yes | ||
| sitemap_url | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose that the tool checks reachability and reports missing/unreachable URLs, which is meaningful. However, it does not explain the 'verify' behavior, whether network requests are made to each known URL, or any side effects such as rate-limit impact or request costs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences cover the operation, inputs, outputs, and practical significance with no filler. The core comparison is front-loaded, and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so describing return values is not necessary. The description is adequate for a straightforward comparison tool, but it omits the semantics of the optional 'verify' parameter and does not provide guidance on how this tool relates to siblings such as audit_urls or check_redirects, which would help an agent choose correctly in more ambiguous cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds some meaning by indicating 'sitemap' maps to sitemap_url and 'list of URLs you know exist' maps to known_urls. However, the 'verify' parameter is entirely unexplained despite being a schema property with a default value, and the mapping from description to parameters remains implicit rather than explicit.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('compare') with clear resources: a sitemap and a list of known URLs. It precisely defines the two reported outcomes—URLs missing from the sitemap and sitemap entries that are unreachable—and the final sentence explains why this matters. It is clearly distinct from siblings like fetch_sitemap or audit_urls.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear scenario for when to use the tool: when you have a sitemap and a separate list of URLs known to exist, such as from a filesystem or crawl. It does not explicitly name alternatives or exclusion conditions, but the context is sufficient for an agent to identify this as the coverage-comparison tool among the siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
4 tool updates
v1.0.0- First observed
audit_urls - First observed
check_redirects - First observed
fetch_sitemap - First observed
sitemap_coverage
TDQS
Scored across 4 tools
Each tool targets a distinct phase of an SEO audit: sitemap fetching, page-level auditing, sitemap coverage comparison, and redirect tracing. The main overlap is that audit_urls already reports redirect chains and broken status codes, which overlaps with check_redirects.
Three tools follow a clear verb_noun pattern (fetch_sitemap, audit_urls, check_redirects), but sitemap_coverage is a noun_noun exception. The inconsistent name is still readable and does not create real confusion.
Four tools is a well-scoped size for a focused SEO audit server. Each tool has a clear job, and there is no redundant filler or overwhelming number of endpoints.
The server covers sitemap parsing, on-page/technical issue auditing, sitemap coverage, and redirects, but it lacks a site-crawling or internal-link-discovery tool, which is needed to find URLs not listed in a sitemap. This is a notable gap for a full audit, though the core workflow is usable with an existing URL list.
Maintenance
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